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Gaussian Quadrature Applied to Eigenvalue Approximations
1982We consider the eigenvalue problem $$Kx = \lambda x,\left( {Kx} \right)\left( s \right) = \int\limits_I {k\left( {s,t} \right)x\left( t \right)dt,I = \left[ {0,1} \right]} $$ (1.1) , with K : X → X, X = L2 (I), a compact integral operator. In order to obtain approximations xh resp. yh for elements of \(N\left( {K,\lambda } \right): = \left\{ {
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Approximation of Functions and Numerical Quadrature
2009The standard treatment of orthogonal polynomials is Szego (1958), in which several other systems are described and more properties of orthogonal polynomials are discussed. A general reference on multivariate orthogonal polynomials is Dunkl and Yu (2001). A type of orthogonal system that I mentioned, but did not discuss, are wavelets.
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Approximate quadratures of the circle. III
Journal of the Franklin Institute, 1879openaire +1 more source
Successive Approximation Applied to Quadrature Formulas
The American Mathematical Monthly, 1960R. A. Struble, R. R. Miller
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Approximating Bayesian Posteriors using Multivariate Gaussian Quadrature
1997Cranfield, John A.L. +5 more
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